Social Media API for Python
Access social media data from any Python application. Use the requests library to pull creator profiles, video analytics, comments, trending content, and more across six platforms with a simple REST API.
Key Features
- Works with the requests library, httpx, or any HTTP client
- Pull profiles, videos, comments, search results, and trending data
- Paginate through large datasets with cursor-based pagination
- Parse JSON responses directly into Python dicts and lists
- Integrate into Django, Flask, FastAPI, or standalone scripts
Code Example
import requests
API_KEY = "your_api_key_here"
BASE_URL = "https://api.creatorcrawl.com/v1"
HEADERS = {"x-api-key": API_KEY}
profile = requests.get(
f"{BASE_URL}/tiktok/profile",
params={"handle": "charlidamelio"},
headers=HEADERS,
).json()
print(f"{profile['user']['nickname']}: {profile['stats']['followerCount']} followers")
videos = requests.get(
f"{BASE_URL}/tiktok/profile/videos",
params={"handle": "charlidamelio"},
headers=HEADERS,
).json()
for video in videos["videos"][:5]:
print(f" {video['desc'][:60]} - {video['stats']['playCount']} views")Getting Started
Get your API key
Sign up at creatorcrawl.com and copy your API key from the dashboard. You get 250 free credits, no card required.
Install requests
Run pip install requests to install the HTTP library. You can also use httpx or urllib3.
Make your first call
Use requests.get() with your API key in the x-api-key header. The base URL is https://api.creatorcrawl.com/v1.
Parse the response
Call .json() on the response to get a Python dict. All endpoints return structured JSON with consistent field names.
Frequently Asked Questions
Which Python HTTP library should I use?
The requests library is the most popular choice and works great. If you need async support, use httpx or aiohttp. Any library that can send HTTP GET requests with custom headers will work.
Is there an official Python SDK?
Not yet, but the REST API is straightforward to use with any HTTP library. The API returns JSON so you can parse responses directly into Python dicts without any special client.
How do I handle pagination in Python?
Endpoints that support pagination return a cursor field and a hasMore boolean. Pass the cursor value as a query parameter in your next request to get the next page of results.
Can I use this with pandas for data analysis?
Yes. Fetch the data with requests, then pass the JSON response directly to pd.DataFrame() or pd.json_normalize() to create a DataFrame for analysis.
What Python version do I need?
Any Python version that supports the requests library works. Python 3.7+ is recommended for modern features like f-strings and type hints.